BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling

6 February 2019

Papers citing "BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling"

50 / 55 papers shown

Title
Evolved Hierarchical Masking for Self-Supervised Learning Zhanzhou Feng Shiliang Zhang 49 0 0 12 Apr 2025
Diffusion Models with Deterministic Normalizing Flow Priors Mohsen Zand Ali Etemad Michael A. Greenspan DiffM 34 2 0 03 Sep 2023
High Fidelity Image Synthesis With Deep VAEs In Latent Space Troy Luhman Eric Luhman DRL 3DV 31 7 0 23 Mar 2023
A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT Yihan Cao Siyu Li Yixin Liu Zhiling Yan Yutong Dai Philip S. Yu Lichao Sun 29 506 0 07 Mar 2023
Discouraging posterior collapse in hierarchical Variational Autoencoders using context Anna Kuzina Jakub M. Tomczak BDL DRL 23 1 0 20 Feb 2023
Where to Diffuse, How to Diffuse, and How to Get Back: Automated Learning for Multivariate Diffusions Raghav Singhal Mark Goldstein Rajesh Ranganath DiffM 27 21 0 14 Feb 2023
Variational Mixture of HyperGenerators for Learning Distributions Over Functions Batuhan Koyuncu Pablo Sánchez-Martín I. Peis Pablo Martínez Olmos Isabel Valera BDL GAN DRL 22 5 0 13 Feb 2023
A Multi-Resolution Framework for U-Nets with Applications to Hierarchical VAEs Fabian Falck Christopher Williams D. Danks George Deligiannidis C. Yau Chris Holmes Arnaud Doucet M. Willetts 16 8 0 19 Jan 2023
Long-horizon video prediction using a dynamic latent hierarchy Alexey Zakharov Qinghai Guo Z. Fountas 28 4 0 29 Dec 2022
Scaling Up Probabilistic Circuits by Latent Variable Distillation Anji Liu Honghua Zhang Guy Van den Broeck TPM 17 24 0 10 Oct 2022
GFlowNets and variational inference Nikolay Malkin Salem Lahlou T. Deleu Xu Ji J. E. Hu Katie Everett Dinghuai Zhang Yoshua Bengio BDL 134 77 0 02 Oct 2022
FusionVAE: A Deep Hierarchical Variational Autoencoder for RGB Image Fusion Fabian Duffhauss Ngo Anh Vien Hanna Ziesche Gerhard Neumann 36 4 0 22 Sep 2022
Fast Lossless Neural Compression with Integer-Only Discrete Flows Siyu Wang Jianfei Chen Chongxuan Li Jun Zhu Bo Zhang MQ 19 7 0 17 Jun 2022
Top-down inference in an early visual cortex inspired hierarchical Variational Autoencoder F. Csikor B. Meszéna Bence Szabó Gergő Orbán BDL DRL 19 5 0 01 Jun 2022
Few-Shot Diffusion Models Giorgio Giannone Didrik Nielsen Ole Winther DiffM 183 49 0 30 May 2022
Novel Applications for VAE-based Anomaly Detection Systems Luca Bergamin Tommaso Carraro Mirko Polato F. Aiolli DRL 19 6 0 26 Apr 2022
BDDM: Bilateral Denoising Diffusion Models for Fast and High-Quality Speech Synthesis Max W. Y. Lam J. Wang Dan Su Dong Yu DiffM 29 92 0 25 Mar 2022
Alleviating Adversarial Attacks on Variational Autoencoders with MCMC Anna Kuzina Max Welling Jakub M. Tomczak AAML DRL 31 12 0 18 Mar 2022
Image Super-Resolution With Deep Variational Autoencoders Darius Chira Ilian Haralampiev Ole Winther Andrea Dittadi Valentin Liévin DRL 30 32 0 17 Mar 2022
Long Document Summarization with Top-down and Bottom-up Inference Bo Pang Erik Nijkamp Wojciech Kry'sciñski Silvio Savarese Yingbo Zhou Caiming Xiong RALM BDL 16 55 0 15 Mar 2022
Model-agnostic out-of-distribution detection using combined statistical tests Federico Bergamin Pierre-Alexandre Mattei Jakob Drachmann Havtorn Hugo Senetaire Hugo Schmutz Lars Maaløe Søren Hauberg J. Frellsen OODD 21 18 0 02 Mar 2022
Benchmarking Generative Latent Variable Models for Speech Jakob Drachmann Havtorn Lasse Borgholt Søren Hauberg J. Frellsen Lars Maaløe 18 3 0 22 Feb 2022
VAEL: Bridging Variational Autoencoders and Probabilistic Logic Programming Eleonora Misino G. Marra Emanuele Sansone 18 21 0 07 Feb 2022
Stay Positive: Non-Negative Image Synthesis for Augmented Reality Katie Z Luo Guandao Yang Wenqi Xian Harald Haraldsson B. Hariharan Serge J. Belongie DiffM 15 5 0 01 Feb 2022
Out of Distribution Detection on ImageNet-O Anugya Srivastava S. Jain Mugdha Thigle OOD 54 5 0 23 Jan 2022
VQ-GNN: A Universal Framework to Scale up Graph Neural Networks using Vector Quantization Mucong Ding Kezhi Kong Jingling Li Chen Zhu John P. Dickerson Furong Huang Tom Goldstein GNN MQ 33 47 0 27 Oct 2021
Likelihood Training of Schrödinger Bridge using Forward-Backward SDEs Theory T. Chen Guan-Horng Liu Evangelos A. Theodorou DiffM OT 174 163 0 21 Oct 2021
Bilateral Denoising Diffusion Models Max W. Y. Lam Jun Wang Rongjie Huang Dan Su Dong Yu DiffM 14 42 0 26 Aug 2021
Sawtooth Factorial Topic Embeddings Guided Gamma Belief Network Zhibin Duan Dongsheng Wang Bo Chen Chaojie Wang Wenchao Chen Yewen Li J. Ren Mingyuan Zhou BDL 32 38 0 30 Jun 2021
The Values Encoded in Machine Learning Research Abeba Birhane Pratyusha Kalluri Dallas Card William Agnew Ravit Dotan Michelle Bao 25 274 0 29 Jun 2021
Score-based Generative Modeling in Latent Space Arash Vahdat Karsten Kreis Jan Kautz DiffM 16 658 0 10 Jun 2021
On Training Sample Memorization: Lessons from Benchmarking Generative Modeling with a Large-scale Competition C. Bai Hsuan-Tien Lin Colin Raffel Wendy Kan 18 34 0 06 Jun 2021
Diagnosing Vulnerability of Variational Auto-Encoders to Adversarial Attacks Anna Kuzina Max Welling Jakub M. Tomczak AAML DRL 26 10 0 10 Mar 2021
Deep Generative Modelling: A Comparative Review of VAEs, GANs, Normalizing Flows, Energy-Based and Autoregressive Models Sam Bond-Taylor Adam Leach Yang Long Chris G. Willcocks VLM TPM 36 480 0 08 Mar 2021
Greedy Hierarchical Variational Autoencoders for Large-Scale Video Prediction Bohan Wu Suraj Nair Roberto Martin-Martin Li Fei-Fei Chelsea Finn DRL 24 99 0 06 Mar 2021
Very Deep VAEs Generalize Autoregressive Models and Can Outperform Them on Images R. Child BDL VLM 31 336 0 20 Nov 2020
Reducing the Computational Cost of Deep Generative Models with Binary Neural Networks Thomas Bird F. Kingma David Barber SyDa MQ AI4CE 18 9 0 26 Oct 2020
A Quaternion-Valued Variational Autoencoder Eleonora Grassucci Danilo Comminiello A. Uncini DRL 20 21 0 22 Oct 2020
Conditional Generative Modeling via Learning the Latent Space Sameera Ramasinghe Kanchana Ranasinghe Salman Khan Nick Barnes Stephen Gould BDL 31 9 0 07 Oct 2020
Self-Supervised Variational Auto-Encoders Ioannis Gatopoulos Jakub M. Tomczak 30 13 0 05 Oct 2020
Detecting Out-of-distribution Samples via Variational Auto-encoder with Reliable Uncertainty Estimation Xuming Ran Mingkun Xu Lingrui Mei Qi Xu Quanying Liu OODD UQCV 39 50 0 16 Jul 2020
IDF++: Analyzing and Improving Integer Discrete Flows for Lossless Compression Rianne van den Berg A. Gritsenko Mostafa Dehghani C. Sønderby Tim Salimans 24 59 0 22 Jun 2020
Denoising Diffusion Probabilistic Models Jonathan Ho Ajay Jain Pieter Abbeel DiffM 116 16,915 0 19 Jun 2020
Augmented Normalizing Flows: Bridging the Gap Between Generative Flows and Latent Variable Models Chin-Wei Huang Laurent Dinh Aaron Courville DRL 31 87 0 17 Feb 2020
Learning Discrete Distributions by Dequantization Emiel Hoogeboom Taco S. Cohen Jakub M. Tomczak DRL 26 31 0 30 Jan 2020
The Usual Suspects? Reassessing Blame for VAE Posterior Collapse Bin Dai Ziyu Wang David Wipf DRL 16 75 0 23 Dec 2019
HiLLoC: Lossless Image Compression with Hierarchical Latent Variable Models James Townsend Thomas Bird Julius Kunze David Barber BDL VLM 13 56 0 20 Dec 2019
Don't Blame the ELBO! A Linear VAE Perspective on Posterior Collapse James Lucas George Tucker Roger C. Grosse Mohammad Norouzi CoGe DRL 14 179 0 06 Nov 2019
Stochastic Latent Actor-Critic: Deep Reinforcement Learning with a Latent Variable Model Alex X. Lee Anusha Nagabandi Pieter Abbeel Sergey Levine OffRL BDL 25 371 0 01 Jul 2019
On the Necessity and Effectiveness of Learning the Prior of Variational Auto-Encoder Haowen Xu Wenxiao Chen Jinlin Lai Zhihan Li Youjian Zhao Dan Pei DRL BDL 18 14 0 31 May 2019